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cloud.google.com·6h ago
AI Research
arXiv CS.AI·27d ago·5 min read
Talking to Me or Someone Else? Rethinking Talk-to-Me Detection in Egocentric Videos
TL;DR
A new approach to talk-to-me (TTM) detection in egocentric videos reformulates the task as an online, frame-level prediction, achieving a 75.5% F1 score. This method incorporates diverse speaking states, enhancing the understanding of social interactions in real-time.
✦ Why It Matters
Implement this frame-level TTM detection model to enhance real-time social interaction analysis in your applications.
Key Takeaways
- Explore the new Online TTM Dataset for training models.
- Utilize multimodal approaches for improved interaction recognition.
- Consider diverse speaking states in your TTM detection systems.
- Evaluate your models against the 75.5% F1 score benchmark.
How It Works
The proposed model leverages a combination of audio, visual, and speech-semantic cues to enhance TTM detection. By analyzing these modalities together, it can better differentiate between various speaking states, such as talking to others or self-talking, in real-time.